Department of Computer Science
University of Toronto

 E.g. reduce to a set of equations governing interactions
 Statistics - measure average behaviour of a very large number of instances
 E.g. gas pressure results from averaging random movements of zillions of atoms
 Error tends to zero when the number of instances gets this large


 E.g. to understand the human body, and the phenomena of ‘life’
 Basic ideas:
 Choosing a boundary
 Describing behaviour
 Treat inter-related phenomena as a system
 Study the relationships between the pieces and the system as a whole
 Don’t worry if we don’t fully understand each piece
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
Department of Computer Science
University of Toronto
Role of the Observer

Achieving objectivity in scientific inquiry
Department of Computer Science

Raw observation is too detailed
1. Eliminate the observer
 We systematically ignore many details
2. Distinguish between scientific reasoning and value-based judgment
 All our descriptions (of the world) are partial, filtered by:
 E.g. the idea of a ‘state’ is an abstraction
 Science is (supposed to be) value-free
 (but how do scientists choose which theories to investigate?)
 Our perceptual limitations
 Our cognitive ability
 Our personal values and experience
For complex systems, this is not possible

 Cannot fully eliminate the observer
 Our observations are biased by past experience




 We look for familiar patterns to make sense of complex phenomena
 E.g. try describing someone’s accent
Achieving objectivity in systems thinking
Redundant - if one observer’s description can be reduced to the other
Equivalent - if redundant both ways
Independent - if there is no overlap at all in their descriptions
Complementary - if none of the above hold
 Any two partial descriptions (of the same system) are likely to be complementary
 Complementarity should disappear if we can remove the partiality
 Study the relationship between observer and observations
 Look for observations that make sense from many perspectives
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
Complementarity:
 Two observers’ descriptions of system may be:
 People react to being studied (Probe effect, Hawthorne effect, etc)

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The principle of complementarity
 E.g. ways of measuring that have no variability across observers

General systems theory
 Originally developed for biological systems:
Describing systems
University of Toronto
But sometimes neither of these work:
 Systems that are too interconnected to be broken into parts
 Behaviour that is not random enough for statistical analysis
Defining Systems
 Elements of a system description
 Example systems
 Purposefulness, openness, hardness, …

How scientists understand the world:
 Reductionism - break a phenomena down into its constituent parts
Basic Principles:
 Everything is connected to everything else
 You cannot eliminate the observer
 Most truths are relative
 Most views are complementary

Department of Computer Science
General Systems Theory
Lecture 8:
What is a system?

University of Toronto
 E.g. ask the observers for increasingly detailed observations
 But this is not always possible/feasible
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© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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University of Toronto
Department of Computer Science
So what is a system?

Elements of a system
Ackoff’s definition:

 The behaviour of each element has an effect on the behaviour of the whole
 The behaviour of the elements and their effect on the whole are interdependent
 However subgroups of elements are formed, each has an effect on the behaviour
of the whole and none has an independent effect on it”

 Weinberg: “A system is a way of looking at the world”
 Systems don’t really exist!
 Just a convenient way of describing things (like ‘sets’)
University of Toronto


Observable Interactions
 How the system interacts with its
environment
 E.g. inputs and outputs
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Subsystems
 Can decompose a system into parts
 Each part is also a system
 For each subsystem, the remainder
of the system is its environment
 Subsystems are inter-dependent
Environment
 Part of the world with which the
system can interact
 System and environment are interrelated
Or, more simply:
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
Boundary
 Separates a system from its
environment
 Often not sharply defined
 Also known as an “interface”
 “A system is a set of two or more elements that satisfies the following
conditions:

Department of Computer Science
University of Toronto

Control Mechanism
 How the behaviour of the system is
regulated to allow it to endure
 Often a natural mechanism

Emergent Properties
 Properties that hold of a system, but
not of any of the parts
 Properties that cannot be predicted
from studying the parts
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
Department of Computer Science
Department of Computer Science
University of Toronto
Conceptual Picture of a System
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Hard vs. Soft Systems
Hard Systems:

The system is…
Soft Systems:

 …precise,
 …well-defined
 …quantifiable

No disagreement about:






The system…
 …is hard to define precisely
 …is an abstract idea
 …depends on your perspective

Where the boundary is
What the interfaces are
The internal structure
Control mechanisms
The purpose ??
Not easy to get agreement
 The system doesn’t “really” exist
 Calling something a system helps us
to understand it
 Identifying the boundaries,
interfaces, controls, helps us to
predict behaviour
 The “system” is a theory of how
some part of the world operates
Examples
 A car (?)

Examples:
 All human activity systems
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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Department of Computer Science
University of Toronto
Types of System

Natural Systems

 E.g. ecosystems, weather, water
cycle, the human body, bee colony,…
 Usually perceived as hard systems

 E.g. set of mathematical equations,
computer programs,…
 Interesting property: system and its
description are the same thing

Source: Adapted from Loucopoulos & Karakostas, 1995, p73
Human Activity Systems

Subject System
Information Systems
 Special case of designed systems
Uses
 Part of the design includes the
representation of the current state of
some human activity system
Symbol Systems
 E.g. MIS, banking systems,
databases, …

Designed Systems
 E.g. cars, planes, buildings,
freeways, telephones, the internet,…
Maintains
information
about
Needs
information
about
 Similarly for abstract and symbol
systems!
 E.g. languages, sets of icons,
streetsigns,…
 Soft because meanings change

Information Systems
 E.g. businesses, organizations,
markets, clubs, …
 E.g. any designed system when we
also include its context of use
Abstract Systems
Department of Computer Science
University of Toronto
Information system
Usage System
Control systems
 Special case of designed systems
 Designed to control some other system
(usually another designed system)
builds
contracts
 E.g. thermostats, autopilots, …
Development System
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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Department of Computer Science
University of Toronto
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
Purposefulness
 Types of behaviours:
Reaction to a stimulus in the environment
Tracks and controls
the state of
Needs to ensure
safe control of
Department of Computer Science
University of Toronto
Control Systems
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The stimulus is necessary and sufficient to cause the reaction
Response to a stimulus in the environment
The stimulus is necessary but not sufficient to cause the response
Autonomous act:
A system event for which a stimulus is not necessary
 Systems can be:
State-maintaining
Subject system
System reacts to changes in its environment to maintain a pre-determined state
E.g. thermostat, some ecosystems
Uses
Goal-directed
System can respond differently to similar events in its environment and can act autonomously in an
unchanging environment to achieve some pre-determined goal state
E.g. an autopilot, simple organisms
Control system
Usage System
Purposive
System has multiple goals, can choose how to pursue them, but no choice over the goals themselves
E.g. computers, animals (?)
builds
contracts
Purposeful
System has multiple goals, and can choose to change its goals
E.g. people, governments, businesses, animals
Development System
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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Department of Computer Science
University of Toronto
Describing System Behaviour
Scoping a system
Source: Adapted from Wieringa, 1996, p16-17


State
 Telephone system - include: switches, phone lines, handsets, users, accounts?
 Desktop computer - do you include the peripherals?
Discrete vs continuous
 a discrete system:
 Tips:
 the states can be represented using natural numbers
 Exclude things that have no functional effect on the system
 Exclude things that influence the system but which cannot be influenced or
controlled by the system
 Include things that can be strongly influenced or controlled by the system
 Changes within a system should cause minimal changes outside
 More ‘energy’ is required to transfer something across the system boundary than
within the system boundary
 a continuous system:
 state can only be represented using real numbers
 a hybrid system:
 some aspects of state can be represented using natural numbers

Choosing the boundary
 Distinction between system and environment depends on your viewpoint
 Choice should be made to maximize modularity
 Examples:
 a system will have memory of its past interactions, i.e. ‘state’
 the state space is the collection of all possible states

Department of Computer Science
University of Toronto
Observability
 the state space is defined in terms of the observable behavior
 the perspective of the observer determines which states are observable

System boundary should ‘divide nature at its joints’
 Choose the boundary that:
 increases regularities in the behaviour of the system
 simplifies the system behavior
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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Department of Computer Science
University of Toronto
Layers of systems
System
University of Toronto
18
Department of Computer Science
Summary: Systems Thinking
Source: Adapted from Carter et. al., 1988,
Subsystems
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
Environment
appropriate for:
Analysis of repair
problems
Wires, connectors,
receivers
Subscriber’s
household phone
system
Telephone calls.
Analysis of
individual phone
calls
Subscribers’ phone
systems
Telephone calls
Regional phone
network
Analysis of regional
sales strategy
Telephone calls
Regional phone
network
National telephone
market and trends
Analysis of phone
company’s long
term planning
Regional phone
networks
National telephone
market and trends
Global communication
systems
© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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© 2004-5 Steve Easterbrook. This presentation is available free for non-commercial use with attribution under a creative commons license.
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